moved more tests to deterministic interface

theano/sandbox/cuda/tests/test_conv_cuda_ndarray.py

@@ -869,5 +869,5 @@ def test_stack_rows_segfault_070312():
     out = theano.shared(numpy.random.rand(1, 2, 2, 3).astype('float32'))
     op = theano.tensor.nnet.conv.ConvOp(imshp=(80, 96, 96), kshp=(9, 9),
             nkern=1, bsize=1)
-    f = theano.function([], [], updates={out: op(img, kern)})
+    f = theano.function([], [], updates=[(out, op(img, kern))])
     f()

theano/sandbox/cuda/tests/test_opt.py

@@ -106,7 +106,7 @@ def test_alloc_memset_0():
 def test_gpuspecifyshape():
     x = cuda.shared_constructor(numpy.ones(3,dtype='float32'), 'x')
     m = theano.tensor.specify_shape(x + numpy.float32(1), (3,))
-    f = theano.function([], updates={x:m * numpy.float32(2)},
+    f = theano.function([], updates=[(x, m * numpy.float32(2))],
                         mode=mode_with_gpu)
     l = f.maker.fgraph.toposort()
     assert not numpy.any([isinstance(x.op, cuda.HostFromGpu) for x in l])

theano/sandbox/cuda/tests/test_var.py

@@ -111,11 +111,11 @@ class T_updates(unittest.TestCase):
 
         up = tensor.unbroadcast(output_var.sum().dimshuffle('x', 'x'), 0, 1)
         output_func = theano.function(inputs=[], outputs=[],
-                                      updates={output_var: up})
+                                      updates=[(output_var, up)])
         output_func()
 
         up = tensor.patternbroadcast(output_var.sum().dimshuffle('x', 'x'),
                                      output_var.type.broadcastable)
         output_func = theano.function(inputs=[], outputs=[],
-                                      updates={output_var: up})
+                                      updates=[(output_var, up)])
         output_func()

theano/sandbox/scan_module/scan.py

@@ -46,17 +46,12 @@ from itertools import izip
 import logging
 import numpy
 
-from theano.compile import SharedVariable, function
-from theano import compile
 from theano import gof
 from theano.tensor import opt, TensorVariable
 from theano.tensor.sharedvar import TensorSharedVariable
 from theano import tensor
-from theano import config
-from theano.updates import Updates
 from theano.scalar.sharedvar import shared as scalar_shared
 from theano.compile.pfunc import rebuild_collect_shared
-import theano
 
 import scan_op
 import scan_utils

theano/tensor/tests/mlp_test.py

@@ -9,7 +9,7 @@ import numpy
 
 import theano
 import theano.tensor as T
-from theano.gof.python25 import any
+from theano.gof.python25 import any, OrderedDict
 
 def gen_data():
 
@@ -293,7 +293,7 @@ def test_mlp():
     # TODO: refine that and include only those
     mode = theano.compile.get_default_mode().including('fast_run')
 
-    updates2 = {}
+    updates2 = OrderedDict()
 
     updates2[classifier.hiddenLayer.params[0]]=T.grad(cost,classifier.hiddenLayer.params[0])
     train_model =theano.function( inputs = [index],

theano/tensor/tests/test_sharedvar.py

@@ -526,8 +526,8 @@ def makeSharedTester(shared_constructor_,
             s = self.cast_value(s)
             s_shared = self.shared_constructor(s)
             f = theano.function([],
-                                updates={s_shared:theano.dot(a_shared,b_shared)
-                                         +s_shared})
+                                updates=[(s_shared, theano.dot(a_shared,b_shared)
+                                         +s_shared)])
             topo=f.maker.fgraph.toposort()
             f()
             #[Gemm{inplace}(<TensorType(float64, matrix)>, 0.01, <TensorType(float64, matrix)>, <TensorType(float64, matrix)>, 2e-06)]
@@ -541,8 +541,8 @@ def makeSharedTester(shared_constructor_,
 
             #now test with the specify shape op in the output
             f = theano.function([], s_shared.shape,
-                                updates={s_shared:theano.dot(a_shared,b_shared)
-                                         +s_shared_specify})
+                                updates=[(s_shared, theano.dot(a_shared,b_shared)
+                                         +s_shared_specify)])
             topo=f.maker.fgraph.toposort()
             shp=f()
             assert numpy.all(shp == (40,40))
@@ -557,8 +557,8 @@ def makeSharedTester(shared_constructor_,
                     b_shared.get_value(borrow=True).shape)
 
             f = theano.function([], s_shared.shape,
-                                updates={s_shared:theano.dot(a_shared,b_shared)
-                                         +s_shared_specify})
+                                updates=[(s_shared, theano.dot(a_shared,b_shared)
+                                         +s_shared_specify)])
             topo=f.maker.fgraph.toposort()
             shp=f()
             assert numpy.all(shp == (40,40))

theano/tests/diverse_tests.py

@@ -8,8 +8,8 @@ import numpy.random
 from theano.tests  import unittest_tools as utt
 
 '''
-  Different tests that are not connected to any particular Op, or functionality of 
-  Theano. Here will go for example code that we will publish in papers, that we 
+  Different tests that are not connected to any particular Op, or functionality of
+  Theano. Here will go for example code that we will publish in papers, that we
   should ensure that it will remain operational
 '''
 
@@ -55,7 +55,7 @@ class T_scipy(unittest.TestCase):
         train = function(
             inputs=[x,y],
             outputs=[prediction, xent],
-            updates={w:w-0.1*gw, b:b-0.1*gb})
+            updates=[(w, w-0.1*gw), (b, b-0.1*gb)])
         predict = function(inputs=[x], outputs=prediction)
 
         N = 4